detect_memory_leak

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations (readOnlyHint: true, idempotentHint: true) already indicate safe, idempotent behavior. The description adds value by noting it 'recognizes modern auto-cleanup patterns...to avoid false positives,' which is useful behavioral context beyond annotations. No contradictions.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences, concise and front-loaded. First sentence gives primary purpose, second adds key detail about auto-cleanup patterns. No redundancy or unnecessary words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

No output schema and no description of return values (e.g., format of leak reports, severity levels, or actionable insights). For a code analysis tool, this is a significant gap. Lacks context on limitations or edge cases (e.g., does it handle all RxJS versions?). Incomplete for AI agent to fully understand what to expect.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents both parameters. The description adds no additional semantic meaning beyond 'analyze for leaks'—it does not explain param constraints, inputs, or variations. Baseline 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Analyze RxJS code for potential memory leaks and subscription management issues.' It specifies the verb (analyze), resource (RxJS code), and goal (detect leaks/issues). It also differentiates from sibling tools like analyze_operators by focusing on memory leaks.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool vs. alternatives like analyze_operators, execute_stream, etc. It does not mention prerequisites, exclusions, or when not to use it. The context implies use for RxJS leak detection, but lacks clear usage boundaries.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.